miivs: Model-implied instrumental variable (MIIV) search

Description Usage Arguments Details Value References See Also Examples

View source: R/miivs.R

Description

A key step in the MIIV-2SLS approach is to transform the SEM by replacing the latent variables with their scaling indicators minus their errors. Upon substitution the SEM is transformed from a model with latent variables to one containing observed variables with composite errors. The miivs function automatically makes this transformation. The miivs function will also identify equation-specific model-implied instrumental variables in simultaneous equation models without latent variables.

Usage

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miivs(model)

Arguments

model

A model specified using lavaan model syntax. See the model argument within the lavaanify function for more information. See the documentation below for a description of how to specify the scaling indicator in latent variable models and impose equality constraints on the parameter estimates.

Details

The miivs function displays a table containing the following information for each equation in the system:

Value

A list of model equations.

References

Bollen, K. A. (1996). An Alternative 2SLS Estimator for Latent Variable Models. Psychometrika, 61, 109-121.

Bentler, P. M., and Weeks, D. G. (1980). Linear Structural Equations with Latent Variables. Psychometrika, 45, 289<e2><80><93>308.

See Also

miive

Examples

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bollen1989a_model <- '

    Eta1 =~ y1 + y2  + y3  + y4  
    Eta2 =~ y5 + y6  + y7  + y8    
    Xi1  =~ x1 + x2 + x3 

    Eta1 ~ Xi1  
    Eta2 ~ Xi1 
    Eta2 ~ Eta1 

    y1   ~~ y5
    y2   ~~ y4
    y2   ~~ y6
    y3   ~~ y7
    y4   ~~ y8
    y6   ~~ y8 
  '

miivs(bollen1989a_model)

zackfisher/MIIVsem documentation built on June 26, 2017, 8:22 p.m.